Distributed Random Number Generation Method on Smart Contracts

Kentaro Sako, Shiníchiro Matsuo, Tatsuya Mori

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We propose N-choice game (NCG), a decentralized pseudo-random number generation method that can be executed on smart contracts. Of the M participants, one is a dealer, and the rest are players, each with a different role. Each participant randomly chooses one value between 0 and N - 1 and receives a score determined by the NCG rule. The amount of reward each participant receives is determined by the score. The values chosen by the participants are combined and hashed into a pseudo-random number. The NCG framework is designed to achieve the following three goals: (1) Incentivize participants to provide random choices, (2) Evaluate the level of randomness in the decentralized environment, and (3) Establish high performance. We implement the NCG framework in Solidity and evaluate its performance. Our extensive experiments revealed that unless more than 90% of NCG players collide, the generated random numbers have high randomness that can pass the NIST randomness test. The experiments also demonstrated that the throughput of random number generation in NCG was 129 times faster than in the existing framework, Random Bit Generator [2].

Original languageEnglish
Title of host publication2022 4th Blockchain and Internet of Things Conference, BIOTC 2022
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450396622
Publication statusPublished - 2022 Jul 8
Event4th Blockchain and Internet of Things Conference, BIOTC 2022 - Virtual, Online, Japan
Duration: 2022 Jul 82022 Jul 10

Publication series

NameACM International Conference Proceeding Series


Conference4th Blockchain and Internet of Things Conference, BIOTC 2022
CityVirtual, Online


  • Smart Contracts
  • blockchain
  • distributed random number generators

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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